To use millions of pieces of data that fly across the Internet. This is the magic power of Big Data. Artificial intelligence then enters the image to find patterns and give meaning to massive and heterogeneous information flows. Together, these two technologies have embarked on a giant mission far from their usual commercial applications: finding treatments for diseases such as cancer.organizations of all types are trying to put a large amount of the data they take to use it well, as are the health care industry and the US federal government.
For decades, scientists have been working towards the ‘holy cup’ to find a cure for cancer. While significant progress has been made, their efforts are often carried out as individual entities. endless shuffling between hospitals, he realized that most of the information recorded about patients was not used. Clinical decisions are often based on clinical trials, that is, in 3% of patients participating in them. This means that the whole experience of what happened to 97% of patients was not used. When we talk about Big Data, we often talk about it in terms of business, and especially how it can be used to make money. But it’s important to remember that the possibilities go further.
Science has the task of expanding the horizon of mankind whether it is by exploring space or discovering more about the small organisms that make up the natural world. But in the Big Data era – a field that emerged thanks to the explosion in the amount of data we made and captured, and sophisticated computer analysis that became possible in recent years – this is more important than before. Actually, there are many databases that allow the sharing of data to enable anyone interested in increasing our knowledge of this field, using data collection. Here are some examples of existing databases to describe a new era of large-scale science. The challenge for cancer research is to explore better all data sets, from tumour biology and clinical information about patients. One of the difficulties is compiling readable files that combine all types of data in a centralized platform to enable interaction. The data volume is very large and is developing very fast. Then it is necessary to utilize, ask complex questions to identify new knowledge in existing data. There is an increasing need for new types of computational analytics.
the origin of cancer in each patient has its own causes. For this reason, treatment will be more effective if they are personal like the disease. This precision medicine is a sequence and analysis of genomes that directs us in that direction. Cancer is not just a single disease, it is a combination of many diseases which was discovered after several decades of research. There is no single liver cancer or one type of pancreatic tumour. It’s no longer just breast cancer, but we know exactly which genes mutate and which ones should be attacked. The next challenge is to find which drugs can treat each mutation.
The patient’s treatment path is not that easy. In theory, an overview of the genetic underpinnings of cancer, made possible by genome sequencing, would allow the most difficult people to treat to benefit from the individual treatment approach. At present, only about 2 per cent of cancer patients have sequenced genomes. Some lucky people are most often treated at elite cancer institutions as part of clinical trials.
However, doctors are increasingly utilizing new technology because it exponentially becomes cheaper and faster. scientists still protect career advancing findings or intellectual property that can be commercialized. Others cite patient privacy issues, especially given the recent series of data breaches in health care organizations. And data that is independent of the name can sometimes still be used to identify patients who are suspected of being anonymous.
Strength in numbers:
More and more scientists believe that collecting and deciphering this torrent of data requires the same open-source ethos as programmed by computer programmers to revolutionize software development. This approach makes the source code of computer programs available openly, and any repairs or modifications to the code are shared publicly. Scientists continue to protect career-advancing findings or intellectual property that can be commercialized.
Others cite patient privacy issues, especially given the recent series of data breaches in health care organizations. And data that is independent of the name can sometimes still be used to identify patients who are suspected of being anonymous. Moving data from one institution to another may be expensive and can take weeks to send a hard drive or download data. Some cancer centres have the resources to invest in computers that are strong enough or networks that are strong enough to support giant datasets.